Identification of the AC and PC are critical for operations such as targeting stereotactic and functional neurosurgery, localisation, analysis in human brain mapping, structure segmentation and labelling in neuroradiology. The Talairach atlas has been widely used as a common standard by neuroscientists and neurosurgeons. To perform spatial normalisation using either standard or modified Talairach transformations, the MSP (midsagittal plane), AC and PC have to be identified.
Currently experts perform the detection of these structures manually. However, observer reproducibility is less accurate and prohibitively time-consuming when large sets of data have to be analysed. Furthermore, there is a certain degree of variability among different experts in tracing these landmarks. For these reasons, there is a need to automate the process of identification with accurate, robust and efficient algorithms.
Sun Y. H. et al, in the article “Anatomic labelling of PET brain images with automatic detection of AC and PC”, J. Digit Imaging, 1998 August; 11 (3 Suppl 1):56-58, describe an automatic detection method for finding the AC and PC from positron emission tomography (PET) brain images. However, the resolution of PET images is very low, and the AC and PC are particularly difficult to identify in such images. Thus, the algorithm is only able to identify the AC and PC with a high level of uncertainty.
Verard L. et al., in the article “Fully Automatic Identification of AC and PC landmarks on Brain MRI using scene analysis”, IEE Trans MI, 16(5), 610:616, 1997, describe a method for automatically finding the AC and PC which assumes that high resolution magnetic resonance imaging (MRI) images are available. An automatic algorithm uses the data to estimate the MSP. In a first stage, two easily detectable structures—the corpus callosum (CC) and brain stem (BS)—are identified using intensity-based recognition. From these, a small structure—the superior colliculus (Co)—is detected. The PC is obtained from the resultant locations using template matching. The position of the AC is then found by a further template matching step. This method suffers from a number of disadvantages, one of which is the need for the high resolution images.